tsne.h

/*
 *
 * Copyright (c) 2014, Laurens van der Maaten (Delft University of Technology)
 * All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 * 1. Redistributions of source code must retain the above copyright
 *    notice, this list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright
 *    notice, this list of conditions and the following disclaimer in the
 *    documentation and/or other materials provided with the distribution.
 * 3. All advertising materials mentioning features or use of this software
 *    must display the following acknowledgement:
 *    This product includes software developed by the Delft University of Technology.
 * 4. Neither the name of the Delft University of Technology nor the names of
 *    its contributors may be used to endorse or promote products derived from
 *    this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY LAURENS VAN DER MAATEN ''AS IS'' AND ANY EXPRESS
 * OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
 * OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
 * EVENT SHALL LAURENS VAN DER MAATEN BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
 * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
 * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
 * BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
 * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING
 * IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY
 * OF SUCH DAMAGE.
 *
 */


#ifndef TSNE_H
#define TSNE_H


template<typename T>
static inline T sign(T x) { return (x == .0 ? .0 : (x < .0 ? -1.0 : 1.0)); }

template<typename T>
T randn();


template<typename T, int OUTDIM>
class TSNE
{
public:
    static int run(T* X, int N, int D, T* Y, T perplexity, T theta, int rand_seed,
             bool skip_random_init, bool verbose, int max_iter=1000, int stop_lying_iter=250, int mom_switch_iter=250);


private:
    static void computeGradient(T* P, unsigned int* inp_row_P, unsigned int* inp_col_P, T* inp_val_P, T* Y, int N, T* dC, T theta);
    static void computeExactGradient(T* P, T* Y, int N, T* dC);
    static T evaluateError(T* P, T* Y, int N);
    static T evaluateError(unsigned int* row_P, unsigned int* col_P, T* val_P, T* Y, int N, T theta);
    static void zeroMean(T* X, int N, int D);
    static void computeGaussianPerplexity(T* X, int N, int D, T* P, T perplexity);
    static void computeGaussianPerplexity(T* X, int N, int D, unsigned int** _row_P, unsigned int** _col_P, T** _val_P, T perplexity, int K, bool verbose);
    static void computeSquaredEuclideanDistance(T* X, int N, int D, T* DD);
    static void symmetrizeMatrix(unsigned int** _row_P, unsigned int** _col_P, T** _val_P, int N);

};




#endif